Discover replayable workflows in an agent's session history (defaults to ~/.claude/projects). Returns each session's transcript path — feed one to reelier_from_session. Only MCP/HTTP tool-call sequences are replayable; native file/shell actions are reported as skipped, never fabricated into a fake result. USE WHEN: deciding which past work is worth compiling into a replayable skill.

Compile a SKILL.md from a session transcript. USE WHEN: the work ALREADY happened (this session or by hand) — recording can't be retroactive. NOT for work that hasn't happened yet (record that live via the reelier mcp proxy). Get the transcriptPath from reelier_scan first. Returns the written skill's path, stats, and open questions — or, honestly, that nothing in the transcript was replayable. If the workflow used a relative time window ("this week"), bind it to a date variable (e.g. {{today-7d}}) so later replays pull the CURRENT window, not a frozen one — the openQuestions output flags this.

Run a skill file at Level 0 (deterministic replay, zero LLM calls) and return the real run record: per-step outcomes, timing, totals, and — when a step drifted — why (the failing assertion). Never fabricates a pass. Reproduces the recorded TOOL CALLS (MCP/HTTP) only — no LLM reasoning or prose step re-runs. It does NOT schedule itself: pair with cron/CI for recurring runs. Pass vars to fill {{templated}} inputs (e.g. a computed date window) so a replay pulls current data. READ-ONLY by default: 'idempotent-write' steps are held back (reported as a refused/failed step) unless you pass allowWrites — so replaying never re-fires a write.

Push a skill's local run records (and, on first push, the skill file) to your receipt ledger, where each receipt gets a shareable permalink + verified-replay badge. Requires REELIER_CLOUD_URL/REELIER_CLOUD_KEY in env — reports skipped-no-key honestly when they're absent. USE WHEN: a run's receipt should be durable or shareable.

Compare two runs of the same skill and report SAME or DRIFTED — the drift-detector for a recorded baseline replayed on a schedule. Compares per-step outcomes, structure, and heal-level from .reelier/runs/.jsonl (defaults to the last two runs); data values that legitimately change run-to-run are NOT drift. Drifted steps carry why (the failing assertion). To check a MODEL upgrade: re-record the workflow with the new model, then diff against your frozen baseline — replaying a pinned skill can't reveal model changes (replay never calls a model). Honest when there aren't two runs yet.